Human body diseases are triggered by a multitude of potential triggering events including environmental pressures, physiological changes, or genetically induced causes, to name a few. The detection of a disease, or disease onset, is paramount to the health of the population and has been an evolving field in modern medicine. One of the more effective methods for detecting a disease is through blood tests. However, recent advances in optics and signal processing have given rise to several non-invasive diagnostic techniques to detect diseases. The non-invasive diagnostic techniques primarily rely on electromagnetic radiation. Based on how the radiation interacts with bodily tissues or analytes, an indication of the presence or absence of a disease state (e.g., cancer, liver disease) can be determined. Various non-invasive diagnostic techniques are known in the prior art; however many techniques provide very limited information about the overall health of the patient. The current non-invasive diagnostic techniques often utilize clunky benchtop devices that are primarily focused on the detection of a single blood analyte, the monitoring of volumetric changes of tissue structures (e.g., plethysmography), or the oxygenation levels of the blood (e.g., pulse oximetry), which are usually directed to the diagnosis or monitoring of a specific disease state. In addition, the current techniques do not provide information about the presence or absence of non-tested diseases, whether the patient experienced a disease triggering event, or the severity of a disease (i.e., disease stage).
Thus, there is a need in the art for a diagnostic eye goggle system capable of collecting and analyzing multiple types of optical data from a user's eye and cross correlate that data with historical data to identify one or more disease states of the user. There is a further need for a diagnostic eye goggle system capable of tracking the biological and physical changes in the eye of a user with or without a disease, and use the tracked changes to identify one or more disease states of a future user.